Genometric analysis of quantitative traits

数量性状的基因组分析

• 批准号: 8149426
• 负责人: alexander f wilson
• 金额: $ 179.85万
• 依托单位: NATIONAL HUMAN GENOME RESEARCH INSTITUTE
• 依托单位国家: 美国
• 资助国家: 美国
• 起止时间: 至
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/8149426
• 关键词: trait

Methods Development Virtually all of the theoretical work during the past year has focused on the development of Tiled regression, linear regression based methods for intra-familial tests of association for quantitative traits that address non-independence both at the marker and observational level. Tiled regression uses both multiple and stepwise regression methods in predefined segments of the genome, defined by hotspot blocks, to identify independent genetic variants responsible for the variation or susceptibility in quantitative and qualitative traits, respectively. Multiple and stepwise methods are used to test for associations on the sequence variants in each tile to select the independent markers within each tile. Higher order stepwise regressions are then used to identify significant variant across tiles, chromosomes and the entire genome. Quantitative and qualitative traits can be analyzed. With this approach, it becomes practical to analyze hundreds of thousands or millions of markers and their significant gene x gene interaction terms. This approach can substantially reduce the total number of tests to a number closer to the number of tiles rather than the number of markers. Furthermore, the tiled approach can be incorporated into a linear regression framework that allows for non-independence between observations incorporating features from the Regression of Offspring on Mid-Parant (ROMP) and Generalized Estimating Equations approaches. The tiled regression methodology has been implemented in TRAP, a software package written in the freely available R language. Functions are provided for assigning SNPs to hotspot-based tiles, data input, analysis and output of results. The package is structured modularly, so that it may be used as a single program or with user-written functions to allow for alternate tile definition or data format. This approach has been applied to both SNP data from fine mapping SNP studies with the scoliosis data in collaboration with Dr. Nancy Miller (U of Colorado), and two targeted candidate gene sequencing projects, an NF1 project in collaboration with Dr. Douglas Stewart and the ClinSeq project, in collaboration with Dr. Les Biesecker. Collaborations Familial Idiopathic Scoliosis Several analyses focusing on candidate regions and phenotypic subsets have been completed and manuscripts have either been submitted or are in preparation. These include: 1) In this study of susceptibility loci in FIS families with at least one individual with a triple curve, candidate regions have been identified on chromosomes 6 and 10 Marosy et al. 2010. 2) Statistical genetic analysis of two sets of families with familial idiopathic scoliosis with characteristics nearly identical to those of the sample analyzed in Miller et al. 2005. Linkage analysis and tests of association were performed in two regions on chromosome 1, previously identified as primary candidate regions. We have identified several regions of interest for subsequent nextgen sequencing Behnemann, doctoral thesis. 3) Targeted sequencing of the IRX gene family in families with kyphoscoliosis. We have identified an association between kyphoscoliosis and a sequence variant in an upstream conserved region of one of the IRX genes. Association analysis resulted in 12 SNPs with p-values < 0.025, of which 11 are 500 kb from IRX1, including the most significant SNP (p = 0.000382). One of these SNPs is in a HCNR sharing 87% sequence identity with a HCNR upstream from IRX3 on 16q12 Justice, in preparation. 4) Statistical genetic analysis of STRPs and SNPs on chromosomes 9 and 16. Fine mapping on chromosomes 9 and 16 was performed to narrow previously identified candidate regions. Linkage and association studies identified several highly significant regions that are candidates for nextgen sequencing Miller et al., in preparation. 5) A study based on the presence of males with severe scoliosis Miller et al., submitted. The males with severe curve subset was comprised of 25 families (207 individuals) in which at least one male was diagnosed in adolescence with a &#8805;30 lateral curvature. The genome-wide linkage analysis for the qualitative and quantitative traits resulted in significant p-values (2 adjacent markers with p-values < 0.01) on chromosomes 2, 16 and 22. Significant SNPs lie primarily in the introns of the LARGE gene, integral to the development and maintenance of skeletal muscle, and SFI1, responsible for the integrity of the chromosomal centromere complex. Other large ongoing collaborations include: 1) Clinical characterization of NF1 (Dr. Douglas Stewart, NIH/NCI) 2) the ClinSeq project (Les Biesecker, NIH/NHGRI) 3) the GeneSTAR project (Drs. Diane and Lewis Becker, Johns Hopkins University School of Medicine) Mathias et al., 2010 4) the India Diabetes Project (Dr. Rasika Mathias, Johns Hopkins University School of Medicine) 5) Variation in metabolites in the Irish (Dr. Larry Brody, NIH/NHGRI)

方法开发 在过去的一年里，几乎所有的理论工作都集中在平铺回归的发展上，基于线性回归的方法用于在标记和观察水平上解决非独立性的数量性状的家族内关联测试。 平铺回归在由热点区块定义的基因组的预定义区段中使用多重和逐步回归方法，以分别识别负责数量和质量性状的变异或易感性的独立遗传变异。 使用多个和逐步方法来测试每个图块中序列变体的关联，以选择每个图块内的独立标记。 然后使用更高阶的逐步回归来识别瓦片、染色体和整个基因组之间的显着变异。 可以分析数量和质量性状。 利用这种方法，分析数十万或数百万个标记及其显著的基因X基因相互作用项变得实用。 这种方法可以大大减少测试的总数，使其更接近于图块的数量，而不是标记的数量。 此外，平铺方法可以被并入线性回归框架中，该线性回归框架允许合并来自中间Parant上的后代回归（ROMP）和广义估计方程方法的特征的观察之间的非独立性。 平铺回归方法已在TRAP中实现，TRAP是一个用免费的R语言编写的软件包。 提供了用于将SNP分配给基于热点的图块、数据输入、结果分析和输出的功能。 该软件包是模块化结构的，因此它可以用作单个程序或与用户编写的函数一起使用，以允许替代瓦片定义或数据格式。 该方法已应用于与Nancy米勒博士（科罗拉多大学）合作的精细SNP研究的SNP数据和脊柱侧凸数据，以及两个靶向候选基因测序项目，一个与道格拉斯斯图尔特博士合作的NF 1项目和与Les Biesecker博士合作的ClinSeq项目。 合作 家族性特发性脊柱侧凸 已经完成了几项侧重于候选区域和表型子集的分析，并已提交或正在编写草稿。其中包括： 1)在至少有一个个体具有三重曲线的FIS家族中的易感基因座的这项研究中，已在6号和10号染色体上确定了候选区域Marosy et al. 2010。 2)两组家族性特发性脊柱侧凸家系的统计遗传学分析，其特征与米勒等人2005年分析的样本几乎相同。 在1号染色体上的两个区域中进行连锁分析和关联测试，这两个区域先前被确定为主要候选区域。 我们已经确定了几个感兴趣的区域，用于随后的下一代测序Behnemann，博士论文。 3)脊柱后侧凸家系中IRX基因家族的靶向测序 我们已经确定了脊柱后凸与其中一个IRX基因上游保守区的序列变异之间的关联。 关联分析得到12个p值<0.025的SNP，其中11个距离IRX1 500 kb，包括最显著的SNP（p = 0.000382）。 这些SNPs之一是在HCNR共享87%的序列同一性与HCNR上游IRX3 16q12正义，在准备。 4)9号和16号染色体上STRP和SNP的统计遗传分析。 对9号和16号染色体进行精细定位，以缩小先前确定的候选区域。 连锁和关联研究鉴定了几个高度显著的区域，其是下一代测序的候选者米勒等人，正在筹备中。 5)米勒等人的一项基于男性重度脊柱侧凸患者的研究，已提交。 严重侧弯男性患者包括25个家系（207名个体），其中至少有一名男性在青春期被诊断为30度侧弯。&#8805; 质量和数量性状的全基因组连锁分析在第2、16和22号染色体上产生显著的p值（2个相邻标记的p值<0.01）。 显著的SNP主要存在于LARGE基因的内含子中，LARGE基因与骨骼肌的发育和维持不可或缺，而SFI 1负责染色体着丝粒复合体的完整性。 其他正在进行的大型合作包括： 1)NF1的临床表征（道格拉斯斯图尔特博士，NIH/NCI） 2)ClinSeq项目（Les Biesecker，NIH/NHGRI） 3)GeneSTAR项目（Drs.Diane和刘易斯Becker，Johns霍普金斯大学医学院）Mathias等，2010 4)印度糖尿病项目（Rasika Mathias博士，约翰霍普金斯大学医学院） 5)爱尔兰代谢物的变化（Larry Brody博士，NIH/NHGRI）